Topic and term search analytics

Abstract

Systems and methods provide for analyzing a group of online articles to identify relevant and popular online articles given a selection of topic(s) and/or term(s). An article score is generated for each online article based on the selected topic(s) and/or term(s) as a function of the relevance of the topic(s) and/or term(s) to the online article and visitor metrics for the online articles. The online articles are ranked based on the article scores, and an indication of the ranked online articles is provided for presentation to the user. In further embodiments, important terms are identified for a selection of topic(s) and/or term(s) based on the most relevant and popular online articles for the selected topics/terms.

What is claimed is: 
     
       1. A computer-implemented method for providing a ranked group of online articles based on a selection of one or more topics and one or more terms, the method comprising:
 receiving the selection of the one or more topics and the one or more terms; 
 generating an article score for each online article from a group of online articles, the article score for a first online article being generated by:
 computing an article topic score for each topic from the one or more topics, each article topic score being computed as a function of a relevance score of a corresponding topic for the first online article and visitor metrics for the first online article, 
 computing a term score for each term from the one or more terms, each term score being computed as a function of a term frequency of a corresponding term in the first online article and the visitor metrics for the first online article, and 
 generating the article score for the first online article as a function of the article topic scores for the one or more topics and the term scores for the one or more terms; 
 
 ranking at least a portion of the online articles based on corresponding article scores to generate the ranked group of online articles; and 
 providing an indication of the ranked group of online articles for presentation to a user. 
 
     
     
       2. The method of  claim 1 , wherein the term score for a first term and the first online article is computed by applying a weighting to at least one selected from the following: the term frequency of the first term in the first online article, and the visitor metrics for the first online article. 
     
     
       3. The method of  claim 1 , wherein the article topic score for a first topic and the first online article is computed by applying a weighting to at least one selected from the following: the relevance score of the first topic for the first online article, and the visitor metrics for the first online article. 
     
     
       4. The method of  claim 1 , wherein the selection of the one or more topics is received via a user selection made from a user interface displaying a plurality of popular topics relevant to the group of online articles. 
     
     
       5. The method of  claim 1 , wherein the visitor metrics correspond to a particular visitor segment. 
     
     
       6. The method of  claim 5 , wherein the particular visitor segment is defined by one or more visitor characteristics specified by the user. 
     
     
       7. The method of  claim 1 , wherein the visitor metrics correspond to a particular time period. 
     
     
       8. The method of  claim 7 , wherein the particular time period is specified by the user. 
     
     
       9. The method of  claim 1 , wherein providing the indication of the ranked group of online articles for presentation to the user comprises:
 generating a user interface providing information regarding the ranked group of online articles; and 
 providing the user interface for presentation to the user. 
 
     
     
       10. One or more computer storage media storing computer-useable instructions that, when executed by a computing device, cause the computing device to perform operations, the operations comprising:
 receiving a selection of one or more topics and one or more terms; 
 generating an article score for each online article from a group of online articles, the article score for a first online article being generated by:
 computing an article topic score for each topic from the one or more topics, each article topic score being computed as a function of a relevance score of a corresponding topic for the first online article and visitor metrics for the first online article, 
 computing a term score for each term from the one or more terms, each term score being computed as a function of a term frequency of a corresponding term in the first online article and the visitor metrics for the first online article, and 
 generating the article score for the first online article as a function of the article topic scores for the one or more topics and the term scores for the one or more terms; 
 
 ranking at least a portion of the online articles based on corresponding article scores to generate a ranked group of online articles; and 
 providing an indication of the ranked group of online articles for presentation to a user. 
 
     
     
       11. The one or more computer storage media of  claim 10 , wherein the visitor metrics correspond to a particular visitor segment defined by one or more visitor characteristics specified by the user. 
     
     
       12. The one or more computer storage media of  claim 10 , wherein the visitor metrics correspond to a particular time period specified by the user. 
     
     
       13. The one or more computer storage media of  claim 10 , wherein providing the indication of the ranked group of online articles for presentation to the user comprises:
 generating a user interface providing information regarding the ranked group of online articles; and 
 providing the user interface for presentation to the user. 
 
     
     
       14. A computer system comprising:
 one or more processors; and 
 one or more computer storage media storing computer useable instructions to cause the one or more processors to: 
 receive a selection of one or more topics and/or one or more terms; 
 compute article scores for a group of online articles based on the one or more topics and/or one or more terms; 
 select a subset of online articles based on corresponding article scores; 
 generate an aggregated term score for each of a plurality of terms in the subset of online articles, the aggregated term score for a first term being generated by:
 computing a term score for the first term for each online article from the subset of online articles, each term score being computed as a function of a term frequency of the first term in a corresponding online article and an article score for the corresponding online article, and 
 summing the term scores for the first term to generate the aggregated term score for the first term; and 
 
 providing an indication of importance of at least a portion of the terms to the one or more topics and/or one or more terms based on the aggregated term scores. 
 
     
     
       15. The system of  claim 14 , wherein the article score for a first online article is computed by:
 when the selection includes one or more topics, computing an article topic score for each of the one or more topics, each article topic score being computed as a function of a relevance score of a corresponding topic for the first online article and visitor metrics for the first online article; 
 when the selection includes one or more terms, computing a term score for each of the one or more terms, each term score being computed as a function of term frequency of a corresponding term in the first online article and the visitor metrics for the first online article; and 
 summing any article topic scores and any term scores to generate the article score for the first online article. 
 
     
     
       16. The system of  claim 14 , wherein the subset of online articles are selected based on corresponding article scores for the subset of online articles exceeding an article score threshold. 
     
     
       17. The system of  claim 14 , wherein the visitor metrics correspond to a particular visitor segment defined by one or more visitor characteristics specified by the user. 
     
     
       18. The system of  claim 14 , wherein the visitor metrics correspond to a particular time period specified by the user.